IPython Interactive Computing and Visualization Cookbook: Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook , Second Edition

Cyrille Rossant

$31.19 ~~$38.99~~

4.4 (7 Ratings)

Paperback Jan 2018 548 pages 2nd Edition

Cyrille Rossant

$31.19 ~~$38.99~~

4.4 (7 Ratings)

Paperback Jan 2018 548 pages 2nd Edition

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Key benefits

• Leverage the Jupyter Notebook for interactive data science and visualization
• Become an expert in high-performance computing and visualization for data analysis and scientific modeling
• A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations

Description

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.

Who is this book for?

This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

What you will learn

• Master all features of the Jupyter Notebook
• Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments
• Visualize data and create interactive plots in the Jupyter Notebook
• Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more
• Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn)
• Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
• Simulate deterministic and stochastic dynamical systems in Python
• Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory

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Amazon verified reviews

User0910 May 13, 2020

Le livre va bien au-delà d'IPython et semble en fait s'adresser au scientifique ayant déjà une pratique de python en lui proposant de mettre à jour ses connaissances sur l'écosystème de Python gravitant en gros autour du calcul numérique.Dans l'absolu, le livre est un peu touche à tout, balayant un nombre impressionnant de librairies en 500 pages, là où une seule pourrait faire l'objet d'un livre séparé. D'ordinaire, ce genre d'inventaire à la Prévert a le don d'agacer pour qui n'aime pas le survol.Or ici, un miracle se produit. Peut-être suis-je exactement le lecteur ciblé par l'auteur, mais quasiment chaque section de chaque chapitre fait mouche. Bien qu'utilisant python régulièrement pour mon travail, je m'aperçois à quel point je reste prisonnier des outils que je connais, et combien je suis ignorant de l'incroyable richesse de l'écosystème scientifique et computationel de python.Je n'ai tout simplement jamais mis la main sur un livre contenant une telle densité informative. Bien sûr, aucun sujet n'est réellement approfondi, mais le plus souvent, les librairies ne sont pas simplement mentionnées, mais utilisées dans un exemple informatif qui met le pied à l'étrier.Chapeau à l'auteur pour ses connaissances et sa maîtrise qui transpirent à chaque page de ce livre impressionnant.

Amazon Verified review

Carol Willing Feb 19, 2018

The "Cookbook" update adds new content about Jupyter and Python 3.6. It provides a comprehensive, yet understandable, reference to Jupyter, IPython, and frequently used Python data science libraries. The code examples clearly demonstrate how to use popular Python libraries with IPython and Jupyter. Each section contains links to additional resources and provides the reader a wealth of high-quality tips and use cases.I highly recommend the "Cookbook" to people getting started with IPython/Jupyter. The examples and content will also delight current users of IPython/Jupyter. An industry standard, the "Cookbook", is now even better with additional content, updates, and color available for visualizations.

gary d. smith Jul 28, 2018

Excellent for my needs as a beginner with Jupyter. very well written. definitely recommend.

Ken Oct 23, 2019

The first half of the first chapter was great, the last two sections hard to understand, the second chapter was good. Will update after finished whole book.

David E. Jun 04, 2018

Very informative cookbook on IPython.

IPython Interactive Computing and Visualization Cookbook: Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook , Second Edition

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